Model predictive Direct Flux Vector Control of multi three-phase induction motor drives

Rubino, S.; Bojoi, R.; Odhano, S.A.; Zanchetta, P.

Abstract

A model predictive control scheme for multiphase induction machines, configured as multi three-phase structures, is proposed in this paper. The predictive algorithm uses a Direct Flux Vector Control scheme based on a multi three-phase approach, where each three-phase winding set is independently controlled. In this way, the fault tolerant behavior of the drive system is improved. The proposed solution has been tested with a multi-modular power converter feeding a six-phase asymmetrical induction machine (10kW, 6000 rpm). Complete details about the predictive control scheme and adopted flux observer are included. The experimental validation in both generation and motoring mode is reported, including post open-winding fault operations. The experimental results demonstrate the feasibility of the proposed drive solution.

Citation

Rubino, S., Bojoi, R., Odhano, S., & Zanchetta, P. (2017, October). Model predictive Direct Flux Vector Control of multi three-phase induction motor drives. Presented at 2017 IEEE Energy Conversion Congress and Exposition (ECCE), Cincinnati, Ohio, USA

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2017 IEEE Energy Conversion Congress and Exposition (ECCE)
• Start Date: Oct 1, 2017
• End Date: Oct 5, 2017
• Acceptance Date: May 1, 2017
• Online Publication Date: Nov 7, 2017
• Publication Date: 2017
• Deposit Date: Mar 16, 2018
• Publicly Available Date: Mar 16, 2018
• Peer Reviewed: Peer Reviewed
• Pages: 3633-3640
• Book Title: Proceedings of the 2017 IEEE Energy Conversion Congress and Exposition (ECCE), Cincinnati, Ohio, USA, 1-5 October 2017
• ISBN: 978-1-5090-2999-0
• DOI: https://doi.org/10.1109/ECCE.2017.8096644
• Keywords: multiphase induction machines; multiphase drives;model predictive control; fault-tolerance; direct flux vector control
• Public URL: https://nottingham-repository.worktribe.com/output/885341
• Publisher URL: http://ieeexplore.ieee.org/document/8096644/
• Contract Date: Mar 16, 2018